Concept
Regression model validation is a critical step to ensure that the model accurately predicts outcomes on new, unseen data, rather than just fitting the noise in the training dataset. It involves techniques such as cross-validation, which help in assessing the model's generalization ability and preventing overfitting, thereby ensuring reliability and robustness in real-world applications.
Relevant Degrees
3